How Do You Protect Your APIs From DDoS Attacks?

Today, DDoS attacks stand out as the most widespread cyber threat, extending their impact to APIs. 

When successfully executed, these attacks can cripple a system, presenting a more severe consequence than DDoS incidents targeting web applications. 

The increased risk amplifies the potential for reputational damage to the company associated with the affected APIs.

How Does DDoS Affect Your APIs?

A DDoS attack on an API involves overwhelming the targeted API with a flood of traffic from multiple sources, disrupting its normal functioning and causing it to become unavailable to legitimate users.

This attack can be particularly damaging as APIs play a crucial role in enabling communication between different software applications, and disruption can impact the overall functionality of interconnected systems.

The impact of DDoS attacks is particularly severe for businesses and organizations that depend on their APIs to deliver essential services to customers. These attacks, employing methods such as UDP floods, SYN floods, HTTP floods, and others, pose a significant threat.

Typically orchestrated through botnets—networks of compromised devices under the control of a single attacker—DDoS attacks can cripple a target’s functionality.

DDoS attacks on APIs focus on the server and each part of your API service. But how do attackers manage to exploit DDoS attacks on APIs?

This Webinar on API attack simulation shows an example of a DDoS attack on APIs and how WAAP can protect the API endpoints. 

Several factors can make APIs vulnerable to DDoS attacks:

Absence or insufficient Rate-Limiting: If an API lacks robust rate-limiting mechanisms, attackers can exploit this weakness by sending a massive volume of requests in a short period, overwhelming the system’s capacity to handle them.

Inadequate Authentication and Authorization: Weak or compromised authentication measures can allow malicious actors to gain unauthorized access to an API. Once inside, they may misuse the API by flooding it with requests, leading to a DDoS scenario.

Insufficient Monitoring and Anomaly Detection: Ineffective monitoring and anomaly detection systems can make identifying abnormal traffic patterns associated with a DDoS attack challenging. Prompt detection is crucial for implementing mitigation measures.

Scalability Issues: APIs that cannot scale dynamically in response to increased traffic may become targets for DDoS attacks. A sudden surge in requests can overload the system if it cannot scale its resources efficiently.

How Do WAAP Solutions Protect Against DDoS Attacks on API?

Web Application and API Protection (WAAP) platform offers in-line blocking capabilities for all layer seven traffic, comprehensively securing web applications and APIs.

To guarantee robust security, WAFs incorporated into WAAP solutions provide immediate defense by filtering, monitoring, detecting, and automatically blocking malicious traffic, thereby preventing its access to the server.

Active monitoring of traffic on an API endpoint enables the identification of abnormal traffic patterns commonly linked to DDoS attacks. Instances of sudden spikes in traffic volume serve as red flags for potential attacks, and a proficient monitoring system can promptly detect and address such increases.

In addition, WAAP enforces rate limits by assessing the number of requests from an IP address. API rate limiting is critical in mitigating DDoS damage and reducing calls, data volume, and types. Setting limits aligned with API capacity and user needs enhances security and improves the user experience. 

To avoid impacting genuine users, find solutions that use behavioral analysis technologies to establish a baseline for rate limiting.

AppTrana WAAP’s DDoS mitigation employs adaptive behavioral analysis for comprehensive defense, detecting and mitigating various DDoS attacks with a layered approach. It distinguishes between “flash crowds” and real DDoS attacks, using real-time behavioral analysis for precise mitigation. This enhances accuracy compared to static rate limit-based systems.